tseffects: Dynamic (Causal) Inferences from Time Series (with Interactions)

Autoregressive distributed lag (A[R]DL) models (and their reparameterized equivalent, the Generalized Error-Correction Model [GECM]) (see De Boef and Keele 2008 <doi:10.1111/j.1540-5907.2007.00307.x>) are the workhorse models in uncovering dynamic inferences. ADL models are simple to estimate; this is what makes them attractive. Once these models are estimated, what is less clear is how to uncover a rich set of dynamic inferences from these models. We provide tools for recovering those inferences in three forms: causal inferences from ADL models, traditional time series quantities of interest (short- and long-run effects), and dynamic conditional relationships.

Version:	0.1.4
Depends:	R (≥ 3.5.0)
Imports:	mpoly, car, ggplot2, sandwich, stats, utils
Suggests:	knitr, rmarkdown, vdiffr, testthat (≥ 3.0.0)
Published:	2025-10-09
DOI:	10.32614/CRAN.package.tseffects (may not be active yet)
Author:	Soren Jordan [aut, cre, cph], Garrett N. Vande Kamp [aut], Reshi Rajan [aut]
Maintainer:	Soren Jordan <sorenjordanpols at gmail.com>
BugReports:	https://github.com/sorenjordan/tseffects/issues
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL:	https://sorenjordan.github.io/tseffects/, https://github.com/sorenjordan/tseffects
NeedsCompilation:	no
CRAN checks:	tseffects results

Documentation:

Reference manual:

tseffects.html , tseffects.pdf

Downloads:

Package source:	tseffects_0.1.4.tar.gz
Windows binaries:	r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries:	r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): tseffects_0.1.4.tgz, r-oldrel (x86_64): tseffects_0.1.4.tgz

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